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In this study, an automatic control technology for liquid-hydrogen zero boil-off was developed to improve the long-term storage capability of small-scale liquefaction systems. An innovative system capable of monitoring both the pressure within the heat pipe and the pressure within the LH 2 vessel was developed. This innovative approach ensures continuous efficiency and reduces downtime, significantly improving the overall performance of the hydrogen liquefaction process. The optimal conditions for automatic control were obtained through a cycle test in ON/OFF mode. In addition, experimental investigations were conducted sequentially to investigate the effect of the water level of liquid hydrogen such as 1st section, 2nd section and 3rd section of LH 2. As a result, these experiments successfully demonstrated zero boil-off of liquid hydrogen for long-term storage in the vessel, corresponding to a constant value in the liquid level meter in each section. The velocity of stabilization from the temperature and pressure perspectives in the vessel increased, and the entire cryocooler cycle time was significantly influenced by the amount of liquid hydrogen produced. • An automatic control technology for liquid-hydrogen zero boil-off was developed. • The pressure data on the liquid hydrogen vessel and heat exchanger were determined. • The effect of the water level of liquid hydrogen was investigated. • Experiments demonstrated zero boil-off of liquid hydrogen for long-term storage. • The entire cryocooler cycle time was influenced by the amount of liquid hydrogen. [ABSTRACT FROM AUTHOR]

This article presents the issues related to the operation and modelling of a ship's main propulsion steam boiler. Such objects are used widely in seagoing ships, especially very large crude oil carriers, as a main propulsion turbine feed. The advantages, along with the simple construction, thus greatly improve reliability making oil feed boilers an excellent source of power for the chosen types of large ships. It is worth mentioning that a vast part of the research work was performed in previous years regarding automatic control of boiler automation, but, since then, this technology has not been the focus of the researchers. Due to the fact that there is little information available on algorithms for controlling ship boilers, in the presented article, the authors created a unique solution for the control system of a propulsion boiler. The proposed control algorithm takes into account the operating parameters of the ship and allows for quick implementation in a simulation system working in a hardware loop, which can be used for quick testing of solutions for boiler systems fed with alternative fuels. In the future, fossil fuels will become less important than they are now, but the control techniques of boilers will eventually change due to different fuel parameters and, therefore, the development of such boilers is necessary. This article presents the results of research collected in real ship boilers during their operation and, based on the results, a digital model of such an object along with the necessary controls was created. This model was implemented into Hardware-In-Loop, which is the initial step for preparing the full model (including sensors, etc.) of a steam-heated boiler. The theoretical background, along with the chosen simulation and experimental results of control implemented into HIL, are presented to validate assumptions. [ABSTRACT FROM AUTHOR]

Featured Application: Featured Application: Automatic control of electrical motors and robotic systems actuated with electrical motors are the main featured applications of this study but are not the limit. Any closed-loop automatic control system with known plant dynamics can be a featured application of this study. In this study, a novel approach of designing automatic control systems with the help of AI tools is proposed. Given plant dynamics, expected references, and expected disturbances, the design of an optimal neural network-based controller is performed automatically. Several common reference types are studied including step, square, sine, sawtooth, and trapezoid functions. Expected reference–disturbance pairs are used to train the system for finding optimal neural network controller parameters. A separate test set is used to test the system for unexpected reference–disturbance pairs to show the generalization performance of the proposed system. Parameters of a real DC motor are used to test the proposed approach. The real DC motor's parameters are estimated using a particle swarm optimization (PSO) algorithm. Initially, a proportional–integral (PI) controller is designed using a PSO algorithm to find the simple controller's parameters optimally and automatically. Starting with the neural network equivalent of the optimal PI controller, the optimal neural network controller is designed using a PSO algorithm for training again. Simulations are conducted with estimated parameters for a diverse set of training and test patterns. The results are compared with the optimal PI controller's performance and reported in the corresponding section. Encouraging results are obtained, suggesting further research in the proposed direction. For low-disturbance scenarios, even simple controllers can have acceptable performance, but the real quality of a proposed controller should be shown under high-amplitude and difficult disturbances, which is the case in this study. The proposed controller shows higher performance, especially under high disturbances, with an 8.6% reduction in error rate on average compared with the optimal PI controller, and under high-amplitude disturbances, the performance difference is of more than 2.5 folds. [ABSTRACT FROM AUTHOR]

This paper investigates a carrier landing controller for unmanned aerial vehicles (UAVs), and a nonlinear model predictive control (NMPC) approach is proposed considering a precise motion control required under dynamic landing platform and environment disturbances. The NMPC controller adopts constraint aware particle filtering (CAPF) to predict deck positions for disturbance compensation and to solve the nonlinear optimization problem, based on a model establishment of carrier motion and wind field. CAPF leverages Monte Carlo sampling to optimally estimate control variables for improved optimization, while utilizing constraint barrier functions to keep particles within a feasible domain. The controller considers constraints such as fuel optimization, control saturation, and flight safety to achieve trajectory control. The advanced control method enhances the solution, estimating optimal control sequences of UAV and forecasting deck positions within a moving visual field, with effective trajectory tracing and higher control accuracy than traditional methods, while significantly reducing single-step computation time. The simulation is carried out using UAV "Silver Fox", considering several scenarios of different wind scales compared with traditional CAPF–NMPC and the nlmpc method. The results show that the proposed NMPC approach can effectively reduce control chattering, with a landing error in rough marine environments of around 0.08 m, and demonstrate improvements in trajectory tracking capability, constraint performance and computational efficiency. [ABSTRACT FROM AUTHOR]

Concrete vibration construction sustains high labor intensity, a poor working environment, difficulties in quality control, and other problems. Current research on concrete vibration focuses on monitoring vibration quality, evaluating vibration processes quantitatively, and assessing mechanical vibration of unreinforced mesh concrete (plain concrete). Standardizing concrete vibration under reinforcing steel mesh remains difficult. There is still a lag in the evaluation of the quality of rework and the consumption of human and material resources. To tackle these issues, a vibrating robotic arm system based on automation control technology, machine vision, and kinematic modeling is proposed. Research and simulation tests on intelligent concrete vibration under reinforcing steel mesh aim to enhance construction efficiency and quality. A five-degree-of-freedom robotic arm with a vision module identifies each rebar grid center in the image, extracts the pixel coordinates, and converts them to the mechanical coordinates by the integration of machine vision algorithms. A vibrator point screening algorithm is introduced to determine actual vibrator point locations based on specific insertion spacing, alongside a vibro-module for vertical movement. Real-time assessment of vibration quality is achieved using the YOLOv5 target detection model. Simulation tests confirm the feasibility of automated concrete vibration control under reinforcing steel mesh by a vibrating robot arm system. This research offers a new approach for unmanned vibration technology in concrete under reinforcing steel mesh, supporting future related technological advancements with practical value. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The performance of manufacturing operations relies heavily on the operators' performance. When operators begin to exhibit signs of fatigue, both their individual performance and the overall performance of the manufacturing plant tend to decline. This research presents a methodology for analyzing fatigue in assembly operations, considering indicators such as the EAR (Eye Aspect Ratio) indicator, operator pose, and elapsed operating time. To facilitate the analysis, a dataset of assembly operations was generated and recorded from three different perspectives: frontal, lateral, and top views. The top view enables the analysis of the operator's face and posture to identify hand positions. By labeling the actions in our dataset, we train a deep learning system to recognize the sequence of operator actions required to complete the operation. Additionally, we propose a model for determining the level of fatigue by processing multimodal information acquired from various sources, including eye blink rate, operator pose, and task duration during assembly operations. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Precision management of medicinal plant production using mechanical systems, processors, and sensors increases productivity, reduces waste, and manages production processes. This research developed a precision harvesting unit equipped with an automatic height adjustment system for utilization in harvesting machines to harvest Hyssop at an optimal height. The unit after development consisted of a power transmission system (converting rotational motion into reciprocating motion), a harvesting platform (cutter-bar, reel, and conveyor), and a system to control the vertical movement of the head. An ultrasonic sensor was employed to detect the highest part of the plant for control purposes. A central control board and a driver generated the control signal, with a stepper motor as the actuator. We measured harvesting-related variables, including dry matter, essential oil content and yield, leaf-tostem ratio, and indices related to conservation agriculture to evaluate the developed precision harvesting unit. Results showed that the unit increased the purity of the harvested plant raw material compared to the manual harvesting of Hyssop, a key to extracting more of the target substances, such as essential oil. The steady-state error of the control system measured 2% in adjusting the cutter-bar height for the optimal height of harvesting Hyssop (T15) in elevation and descension modes. [ABSTRACT FROM AUTHOR]

叶片过滤机是精炼车间脱色工段中非常关键的设备，设备前端后续的工艺阀门很多，有很多操作步骤和时间节点控制阀门的开启和关闭，操作复杂烦琐。为简化人工手动操作的烦琐性及为更多单机系统控制提供技术参考，以立式叶片过滤机为例，采用PLC和触摸屏的方式构建自动控制系统，控制叶片过滤机的单机运行和切换控制。自动控制系统的CPU采用西门子S7-1214C DC/DC/Rly，HMI采用西门子KTP1200触摸屏，并采用西门子TIA PORTAL V18软件进行PLC硬件组态及编程和上位机KTP1200的监控和控制界面的制作，自动控制系统的设计包括两台过滤机的单独控制和切换控制，可根据不同的产量设定切换的时间参数。此系统运行稳定可靠，是独立的控制系统，可以单独应用于生产，还具有以太网通信功能，可以实现与其他控制系统的数据交换。The vane filter is a very critical equipment in the decolorization section of the refining workshop, there are many process valves at the front end and follow-up of the equipment, there are many operation steps and time nodes to control the opening and closing of the valve, and the operation is complex and cumbersome. In order to simplify the tediousness of manual operation and provide technical reference for the control of more stand-alone systems, taking the vertical vane filter as an example, PLC and touch screen were used to build an automatic control system to control the stand-alone operation and switching control of the vane filter. The CPU of automatic control system adopted Siemens 1200 series S7-1214C DC/DC/Rly, HMI adopted Siemens lean series touch screen KTP1200, and Siemens TIA PORTAL V18 software was used for hardware configuration and programming, and the production of monitoring and control interface of host computer KTP1200. The design of the automatic control system includes separate control and switching control of the two sets of filters, and the time parameter of switching can be set according to different outputs. This system operates stably and reliably, and is an independent control system, which can be applied to production alone, also the system has Ethernet communication function, therefore can realize data exchange with other control systems.

In Thailand, vibration problems often occur with rice combine harvester automatic header height adjusting systems. This study aimed to identify parameters for reducing the vibration and managing response time for harvesting speed configuration. An experimental combine harvester header model was designed to automatically adjust three parameters: total movement time, time ratio, and final phase distance within vertical movement ranges of 200, 250, or 300 mm. These parameters were controlled using a proportional flow control valve and a professional learning community (PLC) control unit. The results showed that increased time ratio, final phase distance, and total movement time significantly reduced average vibration amplitude. Higher time ratios corresponded to lower vibration amplitude during changing stages but higher amplitude during stopping stages. Vibration amplitudes during starting, changing, and stopping stages ranged from 0.622 to 1.373 mm, 0.042 to 1.097 mm, and 0.132 to 0.902 mm, respectively, for 200, 250, and 300 mm vertical movement distances. To reduce vibration in the first and second wave phases, precise control of start and final speeds through time ratio and total movement time was necessary. Minimizing the time ratio and final phase distance effectively reduced vibration amplitude in the third wave phase.

The article presents the concepts of control systems that use methods of automatic analysis and interpretation of signals. These issues are presented through the description of three control strategies: simple closed-loop control, control using a process of classification, and using a signal understanding technique. The systems based on the discussed concepts are illustrated with examples of controlling a milling machine and an autonomous vehicle. In addition, in more detail, a task of learning human motor activities is described. This task, due to the nature of the controlled object, which is a human being, is extremely difficult. The article shows that the advanced control process, in which the control algorithm is selected and its parameters are adapted to the current situation, may be implemented through the use of the classification process and machine learning methods in general. Changing the algorithm is also possible using signal understanding techniques. These techniques, utilizing models of the objects, allow to predict the long-term effects of the control process. The ability to build control systems that operate in the above manner is of huge practical importance. The aim of this article is to describe the methods of automatic signal interpretation used in control processes and identify the main problems related to their use. The key problems refer to the acquisition of expert knowledge by the system. In order for this knowledge to be effectively transferred, the methods used in the system should have a high level of explainability. Showing the essential nature of this feature is the main outcome of this work.

The results of a study of the energy efficiency of lighting installations of residential buildings and buildings of social and cultural purpose are given, and based on a technical and economic comparison of four options of lighting systems: with incandescent lamps, fluorescent lamps, compact fluorescent lamps and LED lamps, a quantitative assessment of lighting costs is given. A mathematical model of specific discounted costs was developed, which made it possible to take into account changes in lighting operating conditions over time, and the presentation of research results in relative units gave them a generalized appearance. Conclusions were drawn and recommendations for their application were given. Ref. 9, fig. 2.

The scheme of a bivalent heat pump (BHP) is considered, using both the heat of the water from the return network and the heat of the outside air as low-potential heat sources (LPH). The aim of the work is to create a BHP circuit that provides functioning at the variable heat load temperature. The goal was achieved by solving the following problems: analysis of methods of synthesis of BHP circuits, analysis of circuit operation under random disturbances and development of the automatic control systems for BHP. The most significant result of the work is: a heat pump circuit that can operate at variable pressures of the evaporator and the gas cooler. The next significant result is, for bivalent heat pumps intended for operation in heat supply systems with qualitative and qualitative-quantitative laws of thermal control, the introduction into the heat pump circuit of a heat exchanger installed in the return water circuit of the secondary building and cooled by outside air, as well as two control valves installed in series between the gas cooler and the evaporator, the first valve installed along the refrigerant flow being controlled by a signal based on the pressure difference between the outlet of the gas cooler and the separation vessel between the evaporator and the gas cooler, and the second by pressure in front of the evaporator. The significance of the obtained results lies in the increase of the COP of the heat pump, due to the increase of heat transfer in the gas cooler circuit. The HHP circuit differs from the known ones in that it uses two control valves and the heat exchanger for additional cooling of the return water of the BHP heated building.

The constant development of electronic devices and components allows for older systems (which have been well received) with electronic control of combustion processes in municipal thermal energy to be improved to new levels, with significant economic and ecological effects. This article presents details of the development of an improved natural gas combustion quality control system in the modernized DKVR 6.5-13 steam boiler. This paper presents the results of comparative tests of this boiler obtained for various variants of the system operation. It has been proven that maximum boiler efficiency indicators and minimum toxicity of exhaust gases discharged into the atmosphere can be achieved by using a proposed control system. The system uses the regulated residual chemical underburning method, based on simultaneous control of the oxygen and carbon dioxide content in the exhaust gases. As a result of the use of the proposed method, an increase in boiler efficiency was achieved by 1.5–2.1% compared with standard automatic regulation and an increase by 0.3–0.8% compared with regulation based only on the oxygen content in the exhaust gases. These results were achieved by reducing the excess air coefficient. In addition, nitrogen oxide emissions were reduced by 25–30%, which, with a justified safe carbon monoxide content in exhaust gases of up to 250 ppm, reduced the exhaust gas toxicity index to 20%. [ABSTRACT FROM AUTHOR]

Introduction: The rapid development of electric vehicle technology in the field of renewable energy has brought significant challenges to wireless charging systems. The efficiency of these systems is crucial for improving availability and sustainability. The main focus of the research is to develop an intelligent charging strategy that utilizes fuzzy logic to optimize the efficiency of wireless charging systems for electric vehicles. Method: Introduce a model that combines fuzzy logic algorithm with automatic control system to improve the wireless charging process of electric vehicles. The model adopts dynamic tracking and adaptive control methods by analyzing the characteristics of static wireless charging systems. Utilizing primary phase shift control and secondary controllable rectifier regulation, combined with optimized fuzzy control algorithm. Result and discussion: The experimental results show that when the secondary coil is stable, the model maintains a stable duty cycle of about 75.6% and a stable current of 5A. It was observed that when the mutual inductance values were set to 10, 15, and 20 uH, the efficiency of the primary coil before applying control decreased with increasing resistance. Conclusion: The proposed system has shown great potential for application in real-world electric vehicle charging systems, demonstrating good applicability and feasibility in controlling the charging process and tracking the optimal efficiency point. The integration of fuzzy logic enhances the system's ability to adapt to different operating conditions, which may lead to wider implementation and improved operational efficiency. [ABSTRACT FROM AUTHOR]

The main aspects of the use of automatic monitoring and control systems in order to increase the reliability of power lines are considered. The article highlights modern technologies and techniques that make it possible to quickly identify and prevent possible emergency situations on power transmission lines. The advantages of automated systems compared to traditional monitoring and control methods are discussed, and examples of research and practical applications of such systems are presented. The results obtained can be useful for energy specialists and engineers involved in the design, operation and maintenance of power transmission lines, as well as for developers and manufacturers of automated monitoring and control systems. [ABSTRACT FROM AUTHOR]

Automated welding with robots is one of the core processes of modern manufacturing. Industrial robots are capable of continuously performing welding tasks under different working conditions in well-defined and structured environments. However, reprogramming in the plant is still necessary to deal with uncertainties due to a positioning error of the parts to be welded on the production line. This error can be due to several reasons, including dimensional quality of the parts, mechanical play, aging of the mechanisms, etc. In this sense, an automatic decision-making system is required to compensate for the measured error and avoid stopping the production line. In this work, we propose a controller based on the Enhanced Wagner-Hagras Interval Type-3 NSFLS-1 (EWH Type-3 NSFLS-1), a vision system and a laser beam incident on the plates to be welded to determine the misalignment that is corrected by a fuzzy controller. Type-3 fuzzy logic systems (T3 FLS) make it possible to model the effects of uncertainties and to minimize them by optimizing the parameters during the learning process of the fuzzy system. They can approximate any real continuous function on a compact set to arbitrary accuracy. In this article, several fuzzy logic algorithms were evaluated, resulting in the proposed EWH IT3 TSK NSFLS-1 controller being the best option since it presented the lowest error of 1.79e-09m to successfully reposition the robot. [ABSTRACT FROM AUTHOR]

Copyright of Railway Construction Technology is the property of Railway Construction Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper deals with the application of the Model Predictive Control (MPC) algorithm to the sensorless control of a Permanent Magnet Synchronous Motor (PMSM). The proposed estimation strategy, based on the unscented Kalman filter (UKF), uses only the measurement of the motor current for the online estimation of speed, rotor position and load torque. Information about the system state is fed into the MPC algorithm. The results verify the effectiveness and applicability of the proposed sensorless control technique. To demonstrate its real-world applicability, implementation in low-speed direct drive astronomy telescope mount systems is investigated. The outcomes of the implementation are thoroughly examined, leading to insightful conclusions drawn from the observed results. Through rigorous theoretical analysis and extensive simulation studies, this paper establishes a solid foundation for the proposed sensorless control technique. The results obtained from simulation studies and real-world applications underscore the efficacy and versatility of the proposed approach, offering valuable insights for the advancement of sensorless control strategies in motor applications. The main aim of this work is to demonstrate and validate the practical feasibility of combining two complex techniques, establishing that such an integration is not only possible but also effective in achieving the desired objectives. [ABSTRACT FROM AUTHOR]

In this study, motion of a quadcopter (that is called DRIHA) to track a target is auto controlled based on the data acquired by images. The images are taken by the monocular camera mounted on the center of gravity of the DRIHA. The detected target is automatically tracked by proposed methods. Designed controllers control translational and rotational motion with respect to the motion occurred in images. An image error vector is proposed to reduce the effects of error signals on the motion. Controllers are designed for controlling the pitch, roll, and yaw angles using the features in the image plane. The model developed by the image-based visual servoing (IBVS) approach is tested in the Gazebo simulation environment. Simulation test results validate effectiveness of the proposed system that includes simultaneous and comprehensive designs in terms of automatic control and target tracking performance. The proposed methods enable autonomous navigation applications even in environments where global positioning systems are unavailable. [ABSTRACT FROM AUTHOR]

In order to solve the problems of low correlation between variable fertilizer application system and soil nutrient content detection and insufficient real-time performance, a variable fertilizer application system based on real-time soil nutrient content detection was developed. This paper describes the structure, working principle and design of key components of the soil information acquisition and fertilizer application system. It includes the simulation and analysis of fertilizer application using the discrete element method and the selection of curved blade fertilizer application discs. The system uses STM32F429IGT6 microcontroller and ROS higher-level computer for decision making. The device detects soil nutrients in real time, adjusts the fertilizer motor speed accordingly, and runs autonomously along the planned path. The decision coefficient R2 between the fertilizer application rate and the speed of the fertilizer application wheel is not less than 0.97, and the relative error between the actual fertilizer application rate and the theoretical fertilizer application rate is up to 5.91%, with the maximum value of the coefficient of variation (CV) of 10.18%. The indoor bench test shows that the relative error between the actual fertilizer application rate and the target fertilizer application rate within a single operating grid is up to 6.2%, with the maximum value of CV being 6.64%. The field test in the orchard showed that the maximum relative error between the actual fertilizer application and the target fertilizer application in a single operation grid was 6.3%, and the maximum value of CV was 12.34%, and the fertilizer application was completed in the operation grid, which demonstrated that the device was able to realize real-time and accurate variable fertilizer application according to the soil nutrient information. [ABSTRACT FROM AUTHOR]

Copyright of DYNA - Ingeniería e Industria is the property of Publicaciones Dyna SL and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Intelligent Agriculture Mechanization is the property of Nanjing Institute of Agricultural Mechanization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article presents the concepts of control systems that use methods of automatic analysis and interpretation of signals. These issues are presented through the description of three control strategies: simple closed-loop control, control using a process of classification, and using a signal understanding technique. The systems based on the discussed concepts are illustrated with examples of controlling a milling machine and an autonomous vehicle. In addition, in more detail, a task of learning human motor activities is described. This task, due to the nature of the controlled object, which is a human being, is extremely difficult. The article shows that the advanced control process, in which the control algorithm is selected and its parameters are adapted to the current situation, may be implemented through the use of the classification process and machine learning methods in general. Changing the algorithm is also possible using signal understanding techniques. These techniques, utilizing models of the objects, allow to predict the long-term effects of the control process. The ability to build control systems that operate in the above manner is of huge practical importance. The aim of this article is to describe the methods of automatic signal interpretation used in control processes and identify the main problems related to their use. The key problems refer to the acquisition of expert knowledge by the system. In order for this knowledge to be effectively transferred, the methods used in the system should have a high level of explainability. Showing the essential nature of this feature is the main outcome of this work. [ABSTRACT FROM AUTHOR]

Nowadays, reinforcement learning (RL) is increasingly being employed to optimize automatic control systems. This allows these systems to autonomously learn and improve their operations, enhancing their ability to adapt to changing environments and conditions. However, RL heavily relies on reward signals to guide learning, and in practical tasks, these signals are often sparse. This sparsity hinders the learning procedure as only a small amount of feedback signals are available. Most of the current methods to solve the sparse reward problem need to introduce a lot of hyperparameters, and the sample data utilization is relatively low. To address the issue of sparse rewards in RL-based automatic control systems, we propose the Cosine Attenuation Monte Carlo Augmented Actor-Critic (CAAC) algorithm. CAAC uses a cosine decay function to adjust the Q-value during training, optimizing the effect of final rewards and improving RL algorithm performance in the area of automatic control systems. In addition, we conduct experiments in three simulation environments to validate the proposed approach. The results demonstrate that CAAC outperforms the baseline algorithms in terms of learning speed and obtains 10% to 44.3% higher final reward. [ABSTRACT FROM AUTHOR]

In this work, issues of water separation and purification are addressed, where, in order to achieve the desired results, it is necessary to use several disciplines such as classical physics, biotechnology, automatic control, automation, and applications of industry 4.0. Further, the need for comprehensive and automated solutions for rainwater treatment in the agricultural sector is addressed. This research focuses on designing and implementing a system adapted to these needs using Siemens technologies. The methodology ranges from the design of the Piping and Instrumentation Diagram (P&ID) to the implementation of the interface, incorporating Siemens technologies for data acquisition, electrical connections, treatment programming, and PID controller design. The results show significant advances in the development of the system, highlighting the effectiveness of automation and the HMI-PLC human–machine interface in process monitoring and control. These findings support the viability of a comprehensive rainwater treatment system for the agricultural sector, with important implications for water efficiency, environmental preservation, and increased productivity in agricultural and livestock activities. The contribution of this work is the relationship between engineering and research focused on industrial processes. The scientific contribution is to obtain the dynamic models and apply two strategies to obtain the gains of the PID controller. The first method is performed through the proposal of a Hurwitz polynomial, and the second is performed through genetic algorithms (GA), where they are implemented in a controller that is commonly used in the industry. The technological part includes the integration of work (schemes, programming, and communications) so that the result is as close to what was expected. [ABSTRACT FROM AUTHOR]

Pyrolysis is a process of decomposing material at high temperatures without or with limited air and is an alternative waste treatment which is considered quite prospective to be developed. Plastic waste treatment as pyrolysis fuel, is strongly influenced by operating conditions, which consist of the thermal properties of plastics such as the LDPE type, which are still massively used in society. This research processes LDPE type plastic waste using technology fixed bed pyrolysis type batch reactor with a capacity of 0.01 m³ with initial heating from external heat of LPG energy source. The pyrolysis process takes in a closed reactor and the mass flow rate of the condensate flows naturally to the condenser for the condensation process to become pyro-oil product. Optimization of the reactor pyrolysis was carried out by adding insulated heat cover to reduce heat losses during the heating process. The addition of automatic temperature control to regulate the heating rate, makes operation control easier and reducing fluctuations in temperature distribution during pyrolysis process. The research was carried out with three operating temperature variations of 250, 275, and 300 °C using 0.8 kg LDPE plastic waste for batch test. The performance of automatic temperature control was observed using a digital thermometer and a comparison of the results before and after installation was carried out at a temperature of 300 °C. The results showed that heating temperature control which was previously done manually gives fluctuating results with a temperature difference of up to 50 °C. With the addition of an automatic temperature control system, the operating temperature during the pyrolysis process shows relatively lower fluctuations with a maximum difference of 20 °C. The initial heating energy consumption from LPG and the fuel consumption rate (FCR) show an increase along with the increase in the pyrolysis operating temperature setting.

Industrial robots play a crucial role in a wide range of industrial processes. Because of the complexity of the work environment in which these systems are deployed, more robust and accurate control methods are required. Deep reinforcement learning (DRL) is a comprehensive approach that does not require an initial source of structured data for its learning process. Instead, DRL generates its own data based on its experiences within a work environment. To generate its own data, DRL requires integration with virtualized environments provided by simulators. These tools must include scenarios in industrial contexts and allow integration with machine learning tools, among other capabilities. Currently, several platforms support the simulation of various scenarios and generation of synthetic data, thus facilitating the development of end-to-end systems based on artificial intelligence, such as DRL. This article presents an extensive review of the software tools applied to DRL-based control systems for robotic manipulators. The selection of these tools is based on their efficiency, scalability, and compatibility with contemporary industrial standards and offers insights into their practical application in real-world scenarios. This study established a complete framework for designing and developing control systems for robotic manipulators using end-to-end DRL. This framework outlines the tools in detail, including simulators, APIs, libraries, and methods, and their interactions with each other. Additionally, it discusses the practical implications of this framework, highlighting its potential applications in industry and addressing some of the challenges and limitations encountered in applying DRL to complex robotic systems.

Traffic signal control is an important part of intelligent transportation. Efficient traffic signal control strategies not only alleviate traffic congestion, improve vehicle traffic efficiency, but also reduce exhaust pollution during the waiting period. The traditional multiple intersection signal light control method are generally faced with passive control and can not adapt to complex changes. In view of this, the study first combines reinforcement learning and Markov decision to construct a signal control problem model for multiple intersections. Secondly, deep Q-learning networks are introduced for decision solving, and multi-head attention mechanisms and graph convolutional networks are further introduced for optimization and improvement. Finally, a spatial lightweight model for multiple intersection adaptive graph convolution is proposed. The experimental results show that the maximum throughput of the multi-intersection adaptive control model can reach 195 vehicles/min, the shortest queue length is 4.31 vehicles, the shortest average delay is 1.23 minutes, the shortest average travel time is 2.07 minutes, and the attention value of adjacent intersections is close to 80%. The average green wave time under this model is 4 minutes, and the longest green wave section can reach 5 minutes. It can be seen that the new multi-intersection signal adaptive control model proposed in this study has advantages and feasibility compared with similar methods in various indexes, and can provide new ideas and methods for the further development of traffic signal automatic control technology.

To address the issue of measurement errors in ultrasonic water meters caused by various interfering factors during the flow calibration process, this study proposes a highly automated and intelligent ultrasonic water meter flow calibration system design. Firstly, by analyzing and studying the working principle of the water flow calibration device, and considering the actual flow calibration range, the calibration method that combines the master meter method and the dynamic weighing method is determined. To enhance the automation level of the flow calibration system, the flow calibration control algorithm is thoroughly analyzed and designed. Finally, a flow correction algorithm based on linear interpolation was designed and utilized for water meter flow calibration. Test data show that after the flow correction, the value error of the ultrasonic water meter in the “high area” is not more than 2%, in the “low area” it is not more than 3%, and the repeatability is less than 0.05%. Compared with manual calibration, the flow calibration system designed in this paper enables high-precision automated flow calibration of ultrasonic water meters, significantly enhancing detection efficiency and accuracy.

The article describes the problem of controlling an aircraft control when performing a landing on a curvilinear trajectory. The adoption of a curvilinear approach trajectory allows reducing the impact of air traffic on the areas adjacent to the airport. Performing the correct approach on the curvilinear path requires support. For the correct execution of the landing manoeuvre on the curvilinear track, it is necessary to establish reference points so that the repeatability of the manoeuvre is ensured, especially in the case of landing more than one aircraft at the same time. In the following parts, the landing control system is presented. Particularly carefully presented is the issue of performing tests of the designed control system, which in the case of the aircraft control system during the approach to landing must be extremely thoroughly verified. The test plan included both verification the correctness of the adopted control laws and their robustness to interference occurring as a result of atmospheric air streams. [ABSTRACT FROM AUTHOR]

In the industrial and sales processes, dosing systems of various constructions, whose operation is based on mechanical vibrations (vibratory feeders), are very often used. These systems face many problems, such as resonant frequency, flow instability of dosed product, instability of mechanical vibration amplitude, etc., because most of them are based on controlling the frequency of the electrical signal of the supply voltage. All these factors negatively affect the durability and reliability of the vibratory feeder systems. During this research, an automatic control system for vibratory feeder was created, whose control process is based on the modification of the sinusoidal signal (partially changing the signal area). In addition, such a way of controlling the vibratory feeder is not discussed in the literature. As the research conducted in this paper has shown, while using sinusoidal signal modification it was possible to achieve a stable flow rate of bulk production (the flow rate varied from 0 to 100 g/s when the frequency of mechanical vibrations changed from 1 to 50 Hz) and a stable amplitude of mechanical oscillations was achieved and equal to 1.5 mm. The control system is based on the microcontroller PIC24FV32KA302 for which the special software was developed. The thyristor BTA16 used for voltage modification of the sinusoidal signal made it possible to ensure the reliable control of the sinusoidal voltage modification process. [ABSTRACT FROM AUTHOR]

Considering the degradation of water resources and the increase in human population, desalination seems to be a promising method for meeting the global water demand, from potable water to plant irrigation needs. The contribution of desalination to the agricultural sector, through the supply of water for plants or animals, is critical because this sector represents 70% of the global water demand. Unfortunately, the desalination process is energy-intensive and subjected to several factors that result in undesirable fluctuations on quality/quantity of product water, and/or energy waste. Renewable energy sources can supply the necessary power, but they amplify these challenges because their availability varies over time. A simple and efficient way to tackle this issue is to control the pressure of the feed water before feeding it to the membrane. Typically, the pairing control systems are quite expensive or lack the necessary customization freedom that could improve their operation. Therefore, this study highlights the feasibility of enhancing a typical desalination control equipment via the incorporation of modern low-cost microcontrollers and flexible open-source software; the potential of these tools has not yet been fully explored. The microcontroller executes customized PID logic, driving an industrial inverter module. Our results indicate that the proposed system can keep pace with the desalination process setpoints, reducing the stress of the electromechanical components and periods of out-of-specification freshwater production. This low-level control function implementation minimizes the need for human intervention while providing a promising foundation for further extensions and customizations in this area. [ABSTRACT FROM AUTHOR]

In order to study the influence of discharge parameters on the electric spark deposition process, an automatic electric spark deposition device is built by a closed-loop control system of discharge parameters. An automatic electric spark deposition test is carried out at different control voltages. By analyzing the effective discharge waveform parameters, transfer efficiency, deposition efficiency, contact force in the deposition process, surface morphology, and cross-sectional morphology of the deposition layer under different control voltages, etc. Analysis of the results shows that changing the control voltage has a direct effect on the number of discharge types in the deposition process. With the appropriate control voltage, better transfer efficiency and deposition quality can be achieved. Contact discharge has a greater effect on material transfer efficiency than other types of discharge. The transfer of the electrode to the material on the workpiece is mainly achieved by contact discharge. Automatic control of discharge parameters can also be applied to automatic control of discharge pulse types. [ABSTRACT FROM AUTHOR]

This review paper discusses the development trends of agricultural autonomous all-terrain vehicles (AATVs) from four cornerstones, such as (1) control strategy and algorithms, (2) sensors, (3) data communication tools and systems, and (4) controllers and actuators, based on 221 papers published in peer-reviewed journals for 1960–2023. The paper highlights a comparative analysis of commonly employed control methods and algorithms by highlighting their advantages and disadvantages. It gives comparative analyses of sensors, data communication tools, actuators, and hardware-embedded controllers. In recent years, many novel developments in AATVs have been made due to advancements in wireless and remote communication, high-speed data processors, sensors, computer vision, and broader applications of AI tools. Technical advancements in fully autonomous control of AATVs remain limited, requiring research into accurate estimation of terrain mechanics, identifying uncertainties, and making fast and accurate decisions, as well as utilizing wireless communication and edge cloud computing. Furthermore, most of the developments are at the research level and have many practical limitations due to terrain and weather conditions. [ABSTRACT FROM AUTHOR]

The object of the study is the process of increasing the accuracy of measuring the vessel’s course and course orientation by using the mathematical model of the gyrocompass in the on-board computer. On modern vessels, the gyrocompass is the main course measuring device. Its advantages lie in measuring the current course relative to the geographic meridian, its readings are not affected by magnetic anomalies, as was the case when using magnetic compasses, which led to a partial or complete loss of orientation of control objects. At the same time, gyrocompasses also have their drawbacks. The most significant of them is the inertial deviation of the sensitive element caused by the curvature of the Earth’s surface, a change in course, acceleration or deceleration of the vessel. With the appearance of the moments of these forces, the axis of the gyrocompass leaves the equilibrium position and begins to make precessional movements. To reduce the inertial deviation, constructive solutions and recommendations to shipmasters regarding the consideration of deviational errors are used. Structural solutions lead to an increase in weight, complexity of the design, a decrease in reliability, and an increase in cost. The recommendations of regulatory documents regarding the consideration of the inertial deviation of the sensitive element of the gyrocompass are difficult to implement in practice, but they can be implemented in the on-board computer of the vessel control system by using a mathematical model of the sensitive element. The paper developed a method of increasing the accuracy of gyrocompass course measurement and the accuracy of course orientation by using an observation device built on the basis of a mathematical model of the gyrocompass in the on-board computer of the course control system. This makes it possible to estimate the useful component of course measurement and deviational errors from changes in speed and course, the curvature of the earth’s surface. The useful component, without deviational errors, is used in the vessel’s course control channel. The developed method can be used on vessels, provided it is integrated into the existing automated system of the on-board computer to solve the problem of monitoring the components of the gyrocompass measurement. [ABSTRACT FROM AUTHOR]

The experimental investigations performed in this work and practice have shown that the main defects significantly reducing the service life of enamel-coated pipes are the roughness of the inner surface of a pipe and the presence of small bubbles and layers of macro- and microcracks. The problem of the occurrence of defects in the enamel coating that destroy the integrity of the enamel is considered in this article. The causes of these defects are associated with an incorrect choice of the technological regime when applying an enamel coating to the inner surface of the pipes. The choice of the technological regime on application of a coating depends on the geometric dimensions and technological parameters of the pipes. It is known that imprecise implementation of the technology for applying enamel coatings to the inner surface of pipes effects the formation of microcracks. Taking this into account, the main objectives of this work are to automatically adjust the parameters of the technological regime of the device and to adjust the control system so as to prevent the formation of microcracks during coating application and to improve the automatic regulation of the process. [ABSTRACT FROM AUTHOR]